Research
Published on
Publications
- Real Estate Returns and the Macroeconomy: Insights from Big Data in the U.S., Canada, and the U.K, 2026, with J. Díaz and E. Hansen.
The Journal of Real Estate Finance and Economics, p.1-89.New!
doi10.1007/s11146-025-10045-4 - Forecasting the Volatility of U.S. Oil and Gas Firms with Machine Learning, 2025, with J. Díaz and E. Hansen. Journal of Forecasting, vol. 44, p.1383-1402. doi10.1002/for.3245
- Time-Varying Risk Aversion and International Stock Returns, 2025, with M. Guidolin and E. Hansen. The North American Journal of Economics and Finance, vol. 75, p.102271. doi10.1016/j.najef.2024.102271
- Machine-Learning Stock Market Volatility: Predictability, Drivers, and Economic Value, 2024, with J. Díaz and E. Hansen. International Review of Financial Analysis, vol. 94, p.103286. doi10.1016/j.irfa.2024.103286
- Gold Risk Premium Estimation with Machine Learning Methods, 2023, with J. Díaz and E. Hansen. Journal of Commodity Markets, vol. 31, p. 100293. doi10.1016/j.jcomm.2022.100293
- Economic Drivers of Commodity Volatility: The Case of Copper, 2021, with J. Díaz and E. Hansen. Resources Policy, vol. 73, p. 102224. doi10.1016/j.resourpol.2021.102224
- A Random Walk Through the Trees: Forecasting Copper Prices Using Decision Learning Methods, 2020, with J. Díaz and E. Hansen. Resources Policy, vol. 69, p. 101859. doi10.1016/j.resourpol.2020.101859
Working Papers
- Strategic Competition Timing of Voluntary Disclosure: Evidence from Analyst/Investor Days, 2026, with O. Kolokolova and S. Sarah Zhang.
Latest draft Apr 2026
- Save the Date: Analyst/Investor Days as a Trading Signal, 2026, with O. Kolokolova and S. Sarah Zhang.
Work-in-Progress
- Price Discovery Around Voluntary Disclosure Events, with O. Kolokolova and S. Sarah Zhang.
- Why Is 1/N So Hard to Beat? Adaptive Learning and the Limits of Dynamic Portfolio Choice.